Standard essential patents to boost financial returns

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1 Standard essential patents to boost financial returns Knut Blind 1, Peter Neuhaeusler 2, Tim Pohlmann 3 ABSTRACT Companies financial performance is strongly connected to their innovative capacity which is often based on the development and implementation of advanced or even leading edge technology. Especially in ICT (information and communication technology) markets where technology often overlaps it is crucial to own IPRs (intellectual property rights) to maintain market positions. We measure several indicators of patent value such as forward citation and family size. We especially focus on information on the technology position of a patent, measured by the patent s essentiality to a technology standard. Based on these indicators, we then predict their influence on a company s return on assets. We are able to prove that companies which declare standard essential patents to formal and informal SSOs (standard setting organizations) significantly increase their return on assets. This effect lasts for two years, while coefficients are stronger for patents declared to informal SSOs. We further evidence an inverted U shape distribution and our statistical calculation confirms that there is a threshold for the positive incremental effect of the declaration of essential patents on financial performance. KEYWORDS Standard Essential Patents, Financial Returns, Patent Value 1 Berlin University of Technology, Chair of Innovation Economics, D Berlin Germany, Müller-Breslau- Straße VWS 2, Fraunhofer Institute for Open Communication Systems and Rotterdam School of Management, Chair of Standardisation, Erasmus University. 2 Fraunhofer Institute for Systems and Innovation Research ISI, Breslauer Strasse 48, Karlsruhe, Germany, Tel: +49 (0) , 3 Berlin University of Technology, Chair of Innovation Economics, D Berlin Germany, Müller-Breslau- Straße VWS 2, Tel: +49 (0) , Blog: innovationtomorrow.wordpress.com.

2 Introduction A company s innovative capacity is crucial to maintain competitive advantages in knowledge resources, technology advances, price competitions and market positions. In recent years scholars have increased their examination about the role of intellectual property rights (IPR) on companies market position and financial performance (Hall et al., 2005; Blind et al., 2006; Reitzig and Puranam, 2009). While most of the research examines different factors of patent value, little analysis was conducted that sheds light on the positioning of patents in competitive markets. In fields where technologies and products are complementary, innovation is often overlapping (Graevenitz et al., 2011). Patent protection might thus lead to a so called patent thicket where the commercialization of a technology requires license fees from multiple patentees (Shapiro, 2000; Graevenitz et al., 2011). Especially in the context of standard setting, essential patents can hold-up the use of a technology, even if the patent only protects a minor component (Farrell et al., 2007). Essential patents are those that would be necessarily infringed when a company adopts or implements a standard. Policy makers, legal experts and academics have raised concerns that essential patent holding companies are able to abuse the indispensable character of their patents to control the market. However, most SSOs oblige essential patent holders previous to a standard adoption to sign agreements to license their patents under fair, reasonable and non-discriminatory (F/RAND) or even royalty free (RF) terms. Despite these commitments there is an ongoing discussion about the definition of reasonable licenses (Layne-Farrar, 2007). The goal of standard setting is to commonly agree on the specifications of a technology to be standardized. This is often crucial to enable interoperability and to unlock innovation in complex technologies based on various components provided by different suppliers. However, the process of standard setting can be very costly for participating companies, since standard development seizes employee workforce and creates travel costs for regular meetings and presentations around the world. 4 Companies benefits from standard setting are versatile, such as facilitation of technology and products, strengthening of user confidence and user acceptance and consequently the emergence of new and the growth of already existing markets (Blind, 2004). In the field of ICT stakeholders view positive impacts from standard setting such as increasing product variety and developing global outsourcing opportunities (Blind et al., 2010). Due to the public good character of a standard, these benefits accrue to all companies that are active in the respective market. Some companies 4 As to Chiao et al. (2007) IBM spent more than 500$ million on standard setting expenses, which represents 8,5% of their R&D budget in

3 highly invest in standard setting processes while others do not. Including essential patents in a standard is a practice to recoup a company s investments in standards setting. Yet, there is only little research that examines the impact of standard setting investment on a company s financial performance. Waguespack and Fleming (2009) show that participation in standards consortia increases the likelihood of a buy-out of start-ups, without analyzing performance measurements. Aggarwal et al. (2011) provide empirical evidence of companies participation in standard setting and the influence on returns on stock markets. Our paper extent analysis of participation in standard setting and further examines the impact of investments in standardized technologies on a company s financial performance. While applying valid measurements of patent value such as the average number of forward citations and the average patent family size of a company's patent portfolio (Narin and Noma, 1987; Trajtenberg, 1990), we further add information of a patents inclusion in a standard. We therefore compile over patent declarations from formal SSOs (standard setting organizations) 5 and informal SSOs 6. All organizations provide public databases about patent number, declaration date and company of declaration. We create a data panel built upon company level data and gather information on the total amount of sales, R&D expenditure, number of employees and return on assets per year and per company between 2000 and We use the DTI-Scoreboard 7 dataset including various indicators for 500 companies and their performance from 1990 to 2007 and match these companies to memberships in the above listed formal and informal standard bodies. We thus assure that every company is active in standard setting and is thus able to include their patents into a standard. This data constrain leaves 965 observations for firms. To obtain data on patent characteristics such as forward citations and patent families we use the "EPO Worldwide Patent Statistical Database" (PATSTAT). The financial data of the companies was added from the Standard & Poor s COMPUSTAT Global and COMPUSTAT North America databases. To assess the impact of essential patents on a company s financial performance we conduct a fixed effects panel regression and use return on assets as our explained variable. We 5 ISO, IEC, JTC1-a joint committee of ISO and IEC, CEN/CENELEC, ITU-T, ITU-R, ETSI, and IEEE. 6 IETF, TIA, OASIS, OMA, the Broadband Forum and the MSF Forum. 7 The DTI-Scoreboard is provided annually by the British Department for Innovation, Universities & Skills (DIUS) and the Department for Business, Enterprise & Regulatory Reform (BERR). For the year 2008, it lists the Top 1400 international companies according to their R&D expenditures by industry (the number of companies is smaller in preceding years). In addition to the R&D expenditures, further company-specific values, like sales and the number of employees, are shown. 8 We match these companies to the database of patent declarations. Out of the 157 companies, 85 own essential patents and in sum declare patents to the listed standardization organizations. 2

4 employ the time variant patent characteristics and company information as explanatory variables. Our results give evidence that declaring essential patents to both formal and informal SSOs have a significant positive effect on financial returns. We also include the square of the explanatory variables of essential patents in our regression and find a significant negative effect, which confirms the inverse U-shaped dependency. When comparing the coefficients of our explanatory variables, we further find the impact of essential patents declared in informal standard bodies to be stronger compared to patents in formal standard bodies. To also assess the lasting effect of essential patents on financial returns, we further test models with time lags. The significant level remains robust up until a time lag of two years. Essential patents start to have no significance when lagged by three years or more. The remainder of this paper is structured as follows. In our theoretical section we discuss the measurement of financial performance and patent value indicators. We then describe our database and our methodological approach. Afterwards we calculate different models to test our research question. Finally, we conclude and give implications. Theoretical Background The influence of a company s technology assets on its financial performance is a wide studied field. Analysis of Griliches (1981) and Narin and Noma (1987) were among the first to measure different indicators of patents to influence a company s sales, profits or market value. In the following we will discuss the measurement of financial performance as well as several indicators of patent value and patent positioning. The Return on Assets To assess the value of a company, a large number of indicators have been used hitherto. Within this analysis we intend to focus on the return on assets (ROA) as a measure of the financial performance of companies. ROA is a measure of contemporaneous profitability, or in other words, present day profits. It is formally defined as earnings before interest and taxes π divided by the total assets A of a company. Assuming that a company will live indefinitely and there is no uncertainty, the following relationship is expected to hold for any companyi : ROA = π / A 0i 0i 0i This measure is closely related to another widely used measure for the financial success of a company, namely Tobin's q. Although both are often used as largely equivalent 3

5 metrics in the literature, an important difference exists. Tobin's q takes into account all future profit flows and therefore includes future expectations about earnings, while the ROA is concentrated exclusively on present day profits. As future profit margins are difficult to predict and often reflect herd instinct, speculative bubbles, or other general expectations of the market, we exclusively focus on ROA for our analysis. Patents and Patent Value Indicators Patent applications and patent grants probably are the most important indicators for the technological output of innovation processes within companies, countries and innovation systems in general. Especially in high-tech areas, the number of patents can be assumed to exert a positive influence on the financial performance of a company (Hall et al. 2007). Large patent portfolios, however, not only reflect increased efforts in R&D activities and thus a greater innovative output. A large patent output can also be considered as a positive signal to the market. Furthermore, large patent portfolios are strategically useful, for example, to block other market participants' innovative endeavors or to displace smaller competitors in relevant markets (Blind et al. 2006). Finally, the chances for license or commercial agreements with other companies can be increased and especially in the case of small companies, patents are able to ease the access to the capital market and increase a company's reputation. Since patents, however, differ from one another both in economic and technological value, simple patent counts could lead to a distorted picture of the technological base of a company. Therefore, some additional indicators have been proposed to correct for the quality or value of patents. At the level of company's patent portfolios, especially patent forward citations and family size have proven to be the most promising features to indicate a patent's value (Narin and Noma, 1987; Trajtenberg, 1990). Patent forward citations probably are the most common and widely used indicator to determine the value of a patent (Alcacer et al. 2009; Hall and Ziedonis 2001). The number of forward citations (citations a patent receives) is assumed to measure the degree to which a patent contributes to further developing advanced technology. Therefore, forward citations can be regarded as an indicator of the technological significance of a patent (Albert et al. 1991; Blind et al. 2009). Another important patent characteristic that has been proven to be a useful value indicator at the enterprise level is family size. It is determined by the number of countries or patent offices, at which a patent has been applied (Putnam 1996). For each of these countries, however, application and maintenance fees have to be paid to the respective offices. 4

6 Therefore, an application for a patent in a foreign country means that the applicant tries to secure that market to sell his invention and is prepared to bear additional costs. In this sense, it is assumed that a patentee only files a patent abroad if he expects a corresponding return on the sale of the protected technology. Put simply, a large patent family means a greater market coverage which is associated with preliminary costs. Essential Patents Essential patents are these that a company would necessarily infringe when adopting or implementing a technology standard. Especially in the field of ICT standards may incorporate high technology components which are protected by a large number of patents (e.g. GSM, UMTS, W-LAN, MPEG). While standards have to ensure interoperability and should be open to all interested stakeholders, granted patents provide its holders a temporally limited monopoly right on the technology. In the field of standard setting, companies have to declare IPRs that might affect the standardized technology and agree to license their rights under fair, reasonable and non-discriminatory conditions. These F/RAND agreements are still far from conclusive and there is an ongoing discussion about what a reasonable license for an essential patent should be (Layne-Farrar et. al, 2007). It is still a common believe that essential patent owning companies are able to exploit their positions of technology ownership when standards are commercialized. Indispensible for technology selection in standard setting is the mutual agreement of all participants. The decision to include a patent in a standard is thus a consensus decision and a validation of a patents technological merit. However, Dokko and Rosenkopf (2010) can prove that companies owning patents have a stronger influence on the decisions in standardization processes. Recent literature findings further show that patents increase in their value when they are included in a standard (Rysman and Simcoe, 2008; Layne-Farrar and Padilla, 2011). Bekkers et al. (2001) furthermore give evidence that a company s position in a particular market strongly depends on the number of essential patents. Literature sources show that owning patents in ICT markets (Hall. et al., 2007) and participating in standard setting (Aggarwal, 2011) may increase financial performance. The declaration of a patent to be standard essential requires technical but also cooperative performance of a company. When positioning a patent to be essential to a standard, patent owning companies might be in the position to control whole markets that are established upon the standardized technology. While considering patent value indicators such as citations and 5

7 family size, we believe that companies which declare their patents to be essential tend to have a higher return on assets. We thus derive our basic hypothesis: Hypothesis 1: Essential patents have a positive incremental effect on a company s financial performance in terms of return on assets. Berger et al. (2011) analyze essential patents and show adjustment strategies such as long pendency periods and higher number of amendments in the patent filing process. This proves that companies try to direct their patent claims to be essential to a standardized technology. These strategies demonstrate that patents are only marginally essential to the standard in question. There is further evidence in the literature that essential patents differ in their technological contribution to the standardized technology (Bekkers et al., 2011). An empirical study by Goodman and Myers (2005) evidences over-declaring of essential patents in the field of 3G technologies. Patents of companies that declare a too high number of patents to be standard essential might thus be of less importance. Over declaration also increases patenting cost, especially with long pendency periods. Patent cost increase linear, while we expect a threshold for the positive impact of patent declaration on a company s financial returns. We thus propose the following hypothesis: Hypothesis 2: Over declaring of essential patents has a negative incremental effect on a company s financial performance in terms of return on assets. Patents may be essential to formal or informal standards. Lerner and Tirole (2006) are the first to introduce the option of SSOs selection as a concession parameter in relation to technology ownership. An owner of a strong technology will select an SSO aiming to capture much of users welfare via collecting licensing revenues. In case of a weak technology or the existence of strong alternatives, the technology owner has to make concessions to users, e.g. by signing a royalty free agreement for his patents included in a standard. Chiao et al. (2007) provide empirical evidence for the hypotheses derived from the model on the decision parameters of SSO selection. Companies may thus choose to introduce their technologies to standards in formal or informal SSOs in view of the most beneficial financial returns. 6

8 The standard setting arena is divided into formal and informal SSOs that work on complementary technologies (Blind & Gauch, 2008). Estimations claim that over 60% of all standards in the ICT sector are developed in informal SSOs (Tapia, 2010). Formal and informal SSOs pursue different standardization processes but also differ in their IPR rules. While technology selection in formal standardization is a result of consensus agreement, informal SSOs only demand majority voting. Formal standardization is open to all interested stakeholder, while informal SSO membership is more exclusive. Due to these differences formal standardization is often seen to be more bureaucratic and thus slower in decision making processes, while informal SSOs often face shorter standardization processes (Cargill, 2002). In formal SSOs licensing fees for essential patents are capped by F/RAND commitments. Informal SSOs also allow less restrictive licensing agreements. When considering the finding of Lerner and Tirole (2006), we believe that companies with strong technologies would rather choose informal SSOs where the likelihood of claiming higher royalties and pushing a technology via majority voting is adventurous: Hypothesis 3: The incremental impact of declaring essential patents in informal standards has a stronger effect on companies financial performance compared to patent declarations on formal standards. Patents in the field of ICT may have a strong effect on a company s financial performance (Hall et al., 2007). However, ICT markets are usually subject to short product lifecycles and the survival of technologies is often at pace. We thus believe essential patents to have a limited lasting effect on a company s financial performance: Hypothesis 4: Essential patents have a limited lasting effect on companies financial performance. Data Sources and Variables For the empirical analysis, a panel dataset consisting of 479 companies from 1990 to 2007 based on the DTI-Scoreboard was constructed, including, inter alia, data on R&D expenditures, sales and turnover of the respective companies. The base year for the construction of the dataset is 2001, in which a total of 500 companies were listed in the DTI- 7

9 Scoreboard. Data on previous and following years were in a second step added to that record. If one of the 500 companies had not been listed in the DTI-Scoreboard in the years before or after 2001, the respective observations were treated as missing. Fortunately, each year's scoreboard provides information on the R&D expenditures for the previous four years, so at least some information could be added to fill the gaps. Since some observations are still missing in some time periods, the panel is unbalanced. We further assure that every company is active in standard setting and is thus able to include their patents into a standard. This data constrain leaves 965 observations for 157 companies. In the case of mergers and acquisitions between the companies listed in the DTI- Scoreboard, all data for the respective companies were added. With this method, the companies were treated as if they had already been merged at the beginning of the observation period. This approach was chosen to preserve comparability over time, as the separation of the individual company information is no longer possible after a merger (compare Frietsch, 2006). Mergers and acquisitions with companies that were not listed in the DTI-Scoreboard, however, had to remain uncontrolled. As the DTI scoreboard already contains the most important R&D players, not listed enterprises should be smaller, and therefore distortions should be limited. The relevant information on patenting behavior and the financial performance of companies were added to this database. Relevant patent data were extracted from the "EPO Worldwide Patent Statistical Database" (PATSTAT), which provides information about published patents collected from 81 patent authorities worldwide. The annual sum of patent applications filed by each company in a given year at the European Patent Office (EPO) was calculated. The same was done for the patent value indicators, i.e. for patent forward citations, family size, patent oppositions etc. PCT citations were included if the EPO search report makes reference to the PCT document. All patent data reported are dated by their priorities, i.e. the year of world-wide first filing. The companies were identified via keyword searches. The keywords not only included company names in different spelling variations but also the names of the companies subsidiaries, that are held by the parent company with a direct share of at least 25%. This is to preserve the comparability of patent data with the financial data from the companies balance sheets. Information on the names of the relevant subsidiaries by company was added from the LexisNexis (lexisnexis.com) and Creditreform Amadeus (creditreform.com) databases. We further add information on a patents inclusion in a standard. We therefore extract over patent declarations from formal SSOs such as ISO, IEC, JTC1-a joint committee 8

10 of ISO and IEC, CEN/CENELEC, ITU-T, ITU-R, ETSI, IEEE. In addition, we add patent declarations from informal SSOs such as IETF, TIA, OASIS, OMA, the Broadband Forum and the MSF Forum. All of the listed SSOs provide public databases about patent number, declaration date and company of declaration. 9 In sum, we extract 65,000 patent declarations. Out of the 157 companies of our sample, 85 own essential patents and declare essential patents to the listed SSOs. Formal and informal SSOs differ in their IPR policies and standardization processes. The listed formal SSOs have consistent IPR agreements and standardization rules, while bylaws of informal SSOs may differ. However our differentiation of formal and informal SSOs is also grounded on different outcomes. Formal standards have a formal legitimacy whereas specifications from informal SSOs might be comparable in terms of importance or market acceptance, but still lag the formal accreditation. Lerner and Tirole (2006) find incentive for companies to choose between different forums that benefit the merits of a company s technology. We believe it is thus favorable to measure the impact of essential patent separately for both kinds of organizations. We further add information of a company s participation in a patent pool. This is due to different licensing agreements when companies are pool members (Layne-Farrar and Lerner, 2010). The financial data of the companies like total assets or earnings before interest and tax that are needed to calculate the company's ROA were added from Standard & Poor s COMPUSTAT Global and COMPUSTAT North America databases. All monetary measures were converted to British pounds (GBP) based on a yearly averaged exchange rate which was taken from COMPUSTAT Global Currency database. Descriptive Statistics To better assess the variables of our data set we conduct descriptive statistics. The panel incorporates information on 150 companies and their characteristics in terms of EBIT, sales, employees and R&D investment as well as technological assets such as patents and different value indicators. We further matched our panel with over 65,000 patent declarations from formal SSOs and informal SSOs. Table 1 illustrates the summary statistics of our sample variables. A patent declaration is a statement of a company to own patents that are essential to a standard. This statement is not mandatory and in some cases made after a standard had already been released. Formal patent declarations should not be mistaken for patent 9 E.g

11 disclosures. The latter are obligatory and in most cases not public and a more vague statement ex ante to standardization activities. IP policies of formal SSOs require an IPR statement (patent disclosure) connected to all technical contributions if the existence of patents is possible. These statements are rather broad and there is a chance that the technology will not be selected or only partly accepted. Therefore, not all of the stated patents are essential. Patent declarations in comparison are usually stated ex ante standard release and should thus include only essential patents. However, in most cases the issue of essentiality is not tested from objective authorities (only in the case of a patent pool). We assume that in most cases companies disclose patents at a very early stage of standardization and declare when the agreed technology becomes more distinct. We further assume that the market potential of the standardized technology might be foreseeable to a certain degree. A patent declaration can thus also be interpreted as a commercial interest in the standard. Almost half of the declarations in our database do not indicate the patent number. We matched the declarations with patent numbers to their patent families and solely identified 7318 essential patents. One patent can be declared as being essential to several standards. The number of patent declarations is therefore by far higher than the number of essential patents. We proceed the same way for patent declarations from informal SSOs. However, disclosure policies might differ between informal organizations. A patent pool is a consortium of IPR owners, where companies pool their patents to agree on a single license. A patent pool is a phenomenon that mostly appears in accompaniment of a standardized technology. Patents in patent pools have to pass a test of essentiality for the standardized technology. Since license agreements as well as patent declaration behavior changes when companies enter a patent pool, we matched membership data of 54 patent pools to the companies of our sample. Companies may be member of more than one pool depending on the standardized technology. The number of applications (in thousands) is a count of a company s issued patents per year. The number of patents is an outcome of a company's R&D activity. Patent stock of a company is the sum of the company's issued patents in the last five years, depreciated by 15% each year. This accounts for the fact that knowledge is cumulative. Therefore, it can be assumed that patent stock could exert some additional influence on company market value. The average number of forward citations is the number of forward citations in a four year time window divided by the number of applications with forward citations (also in a 4 year time window). The time window assures that all patents have the same amount of time to be cited. 10

12 The average family size is the average number of distinct patent offices a company's patents were filed at. Variable Mean Std. Dev. Min Max # Obs. # Companies ROA # SDO declarations # pool licensor seats # consortia declarations # patent stock R&D (in m)/sales (in m) Sales (in m)/employees # employees Avg # FW Citations Avg Family Size Table1: Summary statistics of sample variables In addition to the independent variables, some control variables are included in the model. First of all, the number of employees (in thousands) is included to take differences in company size into account. To account for the company s productivity in general, the share of sales (in million GBP) by employee is calculated. To control for increased monetary input into the innovation process, the share of R&D expenditures (in million GBP) divided by sales (in million GBP) is used, which can be regarded as a proxy of how well a company converts results of R&D processes into revenues. To better assess the influence of patent declarations on a company s financial performance we plotted the dispersion of our explained variable return on assets and our two explanatory variables patent declaration in formal and informal SSOs. Figure 1 illustrates that the distribution for both explanatory variables displays an inverted U shape. Companies that have a small number of essential patents and companies that have a high number of declarations seem to have a lower return on assets, although this effect is more pronounced in the case of formal patent declarations. However, we notice that especially in the case of patent declaration in formal standard bodies a small number of 11

13 observations shape the inverted shape U distribution. Interpretation of these results is thus far from conclusive. Figure1: Distribution of companies patent declarations and return on assets We also run a pair wise correlation analysis to further measure correlations among variables of the whole sample. For this purpose we use the cumulative values of patent declaration and pool licensor seats. Company s characteristics and patent value variables are average numbers. As we already expected from the results in Figure 1, there is no linear correlation between return on assets and formal and informal patent declarations. A company s patent stock as well as the average number of employees is positively connected to the return on assets. These results could be the result of a size effect: companies that have stronger human and technology capital have a higher ROA. R&D investment in comparison has a weak negative effect. Both patent value indicators seem to work well as they positively correlate with a company s financial performance. Due to the inverted U shape distribution of our explained variable and several effects that correlate with ROA we need to conduct a multivariate analysis to find more conclusive results. 12

14 1 ROA 1 2 formal patent dec. 3 pool licensor seats 4 informal patent dec. 5 patent stock 6 av. R&D (in m) 7 av. # employees 8 av. # FW- Citations 9 Avg Family Size *** *** 0.09*** 0.38*** 0.10*** ** 0.06*** -0.07** 0.16*** 0.06*** *** *** *** -0.23** *** ** -0.04** -0.06** 0.05** -0.09** *** ** ** ** 0.28** Note: Variables formal and informal declarations and pool licensor seats are cumulative values. R&D expenditure and # employees are average numbers. Significance Level: ***p<0.01, **p<0.05, *p<0.1 Table 2: Pair wise correlation matrix of sample variables Empirical Analysis In order to estimate the effects patents standard essentiality on company performance as measured by ROA, we use fixed effects panel regression with cluster robust standard errors by company. Since the data used for the analysis is in the form of a company-level panel, the econometric specifications have to take account of the typical peculiarities of this data structure. If models are subject to unobserved heterogeneity, which is correlated with the explanatory variables, simple Pooled OLS estimators are asymptotically biased. To account for this problem linear panel-data models are used in order to eliminate time constant unobserved heterogeneity. To decide between fixed or random-effects, a Hausman-Test was employed. It shows that the random-effects assumption that explanatory variables are uncorrelated with company-specific effects is violated, which would lead to systematically biased standard errors. Therefore, only a fixed-effects (FE) estimator leads to unbiased estimates, although we have to keep in mind that the fixed-effects estimator cannot control for time-invariant covariates. 13

15 In particular, the linear panel-data model is as follows: y = x β + c + u i = 1,..., n t = 1,... T it it i it Where yit is the explained variable of unit i in periodt, xit is a vector of explanatory variables, β is a coefficient vector, ci is a company-specific effect and uit idiosyncratic errors. We calculate three models in our multivariate analysis by including and excluding different control variables. Proceeding this way we try to capture the influence of companies varying investments (R&D expenditure), assets (patent applications, employees) or performance (sales). We thus want to isolate the effect of our main explanatory variable of patent positioning (standard essential) and patent value (forward cites, family size). Multivariate Results In Table 3 the empirical results are presented. In M2 and M3 our statistical tests show that R&D productivity (R&D expenditures/sales) has a significant negative influence on ROA. This negative effect can be explained by the characteristic of our variable. R&D investments are costs which might pay off several year later. For example, a company invests in new innovative processes or technologies. Yet, it is unsure whether or not these investments are successful and contribute to a company s performance. R&D investments are above all costs which consequently have a negative effect on the ROA. In comparison, our variable of labor productivity shows significant positive results. Sales per employees is a good measure to account for a company s labor efficiency. When including the number of patent applications we have no significant effects. These results once more evidence that it is not sufficient to solely account for a company s technological performance by solely measuring the number of patent filings. We thus also included patent value indicators in our third model. However, in our estimation the patent family size has no effect on ROA and the number of forward cites is even negatively correlated to our explained variable. Our main explanatory variables are patent declarations. There has been evidence in the literature that forward cites are positively connected to patents which are essential to a standard (Rysman and Simcoe 2008; Layne- Farrar and Padilla, 2011). We thus believe that the patent value effects are capture by our main explanatory variable, patent declaration. There is also no effect of the number of pool licensor seats that a company of our sample holds. However, in order to become a pool member companies have to declare their essential patents. Once a firm is a pool member the declaration behavior is thus default. The pool variable is used to control this effect. 14

16 DV=ROA M1 M2 M3 Coef. S/E Coef. S/E Coef. S/E # formal *** *** *** patent declarations 1 # formal *** *** *** patent declarations sq 2 # pool licensor seats 1 # informal * ** ** patent declarations 1 # informal * ** ** patent declarations sq 1 # patent applications R&D (in *** *** m)/sales (in m) Sales (in ** ** m)/employees # employees Avg # FW * Citations Avg Family Size Constant *** *** *** Time- YES YES YES Dummies Number of companies Observations R² within F 6.06 *** 9.73 *** 9.02 *** Note: 1 Coefficient multiplied by 1,000 to make effects visible. 2 Coefficient multiplied by 1,000,000 to make effects visible. The difference in the number of observations can be explained by the fact that we use an unbalanced panel, in which data for some observations in the respective years could be missing. Significance Level: ***p<0.01, **p<0.05, *p<0.1 Table 3: Results of the fixed-effects panel regression models All of our three models confirm the positive effect of our explanatory variables patent declarations in formal and informal SSOs. We are able to confirm our first hypothesis H1: Companies patents which are essential to a formal or informal standard significantly increase the ROA. We also included the square number of declarations to account for the inverted U shape dispersion as to Figure 1. Our empirical findings further confirm our second hypothesis 15

17 H2: The squared number of patent declarations has a significant negative effect on ROA. Results prove our assumption that owning a too high number of standard essential patents has a negative effect on ROA. Companies may be able to choose to participate in different SOOs depending on the strength of their technology and assumptions of technology returns (Lerner and Tirole, 2006). We believe that the ability to influence technology selection is superior in informal SSOs. Furthermore ex ante commitments to license essential IPR are less restrictive in informal SSOs. We thus concluded that a company with strong technology assets rather declares its patents to informal SSOs. Our results prove the stronger positive effect of declaring patents to informal SSOs. We thus confirm H3: The incremental impact of declaring essential patents in informal standards has a stronger effect on companies financial performance compared to patent declarations on formal standards. In our theoretical section we argued that owning essential patents may enable a company to control markets. Thus, we expect the consequence of patent declarations to also have a lasting effect. We calculate M3 again but lag the number of patent declarations by one, two and three years (Table 4). Our results still measure the positive effect of patent declarations and the negative correlation for the square variable. Findings are robust up until a time lag of two years. The effect is gone for lags from three years or longer. We expected that the incremental influence of patent declaration has a lasting effect. We further hypnotized that this effect is limited due to short product lifecycles in the ICT sector. Our results thus also confirm our fourth hypothesis H4: Essential patents have a limited lasting effect on companies financial performance. Table 4 further gives evidence on the development of the coefficients of our explained variable. Coefficients remain to be stronger in the case of informal patent declaration. However, in the dynamic comparison we can observe that coefficients constantly decrease in the case of formal SSOs and increase in the case of informal SSOs up until a lag of one year. We believe these dynamic differences are connected to different standardization processes. Informal SSOs might be able to standardize technology in earlier stages (Cargill, 2011). Patents might thus still increase in their value while the technology is yet emerging. Our results prove this effect for the case of financial returns. 16

18 DV=ROA M3 lagged 1 year M3 lagged 2 years M3 lagged 3 years Coef. S/E Coef. S/E Coef. S/E L.# formal * *** patent declarations 1 L.# formal * * patent declarations sq 2 L.# pool licensor seats 1 L.# informal * * patent declarations 1 L.# informal *** *** *** patent declarations sq 1 # patent applications R&D (in *** *** *** m)/sales (in m) Sales (in ** ** m)/employees # employees Avg # FW Citations Avg Family Size Constant * Time- YES YES YES Dummies Number of companies Observations R² within F 21.9 *** *** *** Notes: 1 Coefficient multiplied by 1,000 to make effects visible. 2 Coefficient multiplied by 1,000,000 to make effects visible. The difference in the number of observations can be explained by the fact that we use an unbalanced panel, in which data for some observations in the respective years could be missing. L. means that the variable is lagged. Significance Level: ***p<0.01, **p<0.05, *p<0.1 Table 4: Results of the fixed-effects panel regression models with lagged explanatory variables Conclusion The financial performance of companies operating in technology markets is always connected to companies technological capabilities or technological resources. Situations of divided 17

19 technological leadership require companies to maintain market positions by protecting technological assets with IPRs. Most companies own big patent portfolios to protect their innovations or to block competitors in the market. The number of patent applications and patent grants is a common indicator to measure technological output of a company. Large patent portfolios, however, not only reflect increased efforts in R&D activities and thus a greater innovative output. Patents may differ from one another both in economic and technological value. Simple patent counts could lead to a distorted picture of the technological base of a company. Our paper seeks to assess not only technological patent value indicators, but also the strategic positioning of a patent. Therefore we measure the influence of standard essential patents on a company s ROA. Essential patents are these that one would necessarily infringe when the standard is implemented or adopted. Companies that own essential patents have a certain market control since they could possibly block whole technologies. Our paper assesses these patent characteristics and measures their influences on a company s financial performance. We built up a comprehensive dataset of company characteristics such as human capital (employees), financial performance (sales), technological investment (R&D expenditure) and technological assets (patent portfolio). We further connect these data to more precise measures of technological capabilities such as measuring the value of the patents (forward citations, family size) and the positioning of the patent (standard essentiality). We explain the financial performance of a company (return on assets) in a dynamic model. Our results show positive results for the declaration of essential patents in formal and informal SSOs. These incremental effects on a company s return on assets last up until two years. The effect of patent declarations in informal standards is significantly stronger. However, our results are negative when we include the square number of our explanatory variables. These finding indicate an inverted U shape correlation of essential patents and a company s financial performance. We prove that companies which declare a too high number of essential patents deteriorate in their financial performance. Our findings evidence the incremental effect of patent declaration on a company s ROA. Especially interesting is the lasting effect of our models. Results from other empirical studies have shown that the patent declaration timing is not always connected to the first release of a standard. Actually, a large number of patent declarations are declared ex post standard release (Blind et al., 2011; Layne-Farrar, 2011). This is due to the dynamic evolvement of technology standards, where technological development also takes place after the first emergence of a standard. Standards can be extended by further versions or are 18

20 updated by amendments, which might incorporate new technologies and thus new patents. Even though companies might have filed the patents in question several years before, we believe the timing of declaration has a signaling effect. When companies declare that they have essential patents included in a standard, they signal technological competence and market power. Our results prove that a company s current and also new future financial performance is connected to these signaling effects. In comparison, when company s claim to have a too high number of essential patents, markets might value these circumstances as lock-in situations. When a technology is subject to a high number of patents and when one company has a too high share of essential patents on a technology, market acceptance of the standard decreases. As a consequence these companies seem to even aggravate in their financial performance. When comparing the coefficients of our models we have higher values for the patent declaration for informal standards. The lasting effect increases for informal standards up until one year lag, while the positive effect constantly decreases for declarations on formal standards. Informal standardization is often subject to quicker processes, while they lack a formal accreditation. The technical evolvement and market acceptance might thus take longer as for formal standards. In some cases informal standards are even accredited to formal standards. Our findings of the lasting effects of patent declaration might thus be subject to these processional differences. References Aggarwal, N.; Dai, Q.; Walden, E. A The More, the Merrier? How the Number of Partners in a Standard-Setting Initiative Affects Shareholder s Risk and Return, MIS Quarterly, (35: 2) pp Albert, M.B., Avery, D., Narin, F., McAllister, P Direct validation of citation counts as indicators of industrially important patents, Research Policy, 20 (3), Alcacer, J., Gittelman, M., Sampat, B Applicant and examiner citations in U.S. patents: An overview and analysis, Research Policy, 38, Bekkers R, Duysters G, Verspagen B Intellectual property rights, strategic technology agreements and market structure. The case of GSM, Research Policy; 31; Bekkers, R., Bongard, R. & Nuvolari, A An empirical study on the determinants of essential patent claims in compatibility standards, Research Policy, forthcoming. 19

21 Berger, F., Blind, K., Thumm, N Filing behaviour regarding essential patents in industry standards, Research Policy, forthcoming. Blind, K The Economics of Standards: Theory, Evidence, Policy. Blind, K., Thumm, N Interrelation between patenting and standardization strategies: empirical evidence and policy implications, Research Policy 33, Blind, K., Edler, J., Frietsch, R., Schmoch, U Motives to patent: Empirical evidence from Germany, Research Policy, 35, Blind, K., Gauch, S Trends in ICT standards: The relationship between European standardization bodies and standards consortia, Telecommunications Policy, Volume 32, pp Blind, K., Gauch, S., Hawkins, R How stakeholders view the impacts of international ICT standards, Telecommunications Policy, Volume 34, Pages Blind, K.; Bekkers, R.; Dietrich, Y.; Iversen, E.; Müller, B.; Pohlmann, T.; Verweijen, J EU Study on the Interplay between Standards and Intellectual Property Rights (IPR), commissioned by the DG Enterprise and Industry, in press. Chiao, B., J. Lerner, J. Tirole The rules of standard setting organizations: An empirical analysis. The RAND Journal of Economics. 38(4), pp Dokko, G., Rosenkopf, L Social Capital for Hire? Mobility of Technical Professionals and Firm Influence in Wireless Standards Committees, Organization Science Vol. 21, No. 3, May-June 2010, pp Griliches, Z Market Value, R&D and Patents, Economics Letters, 7, 187. Farrell, J., J. Hayes, C. Shapiro, and T. Sullivan Standard setting, patents and holdup. Antitrust Law Journal 74, pp Frietsch, R Micro data for macro effects. In: Hingley, P./Nicolas, M. (eds.): Forecasting Innovations. Methods for Predicting Numbers of Patent Filings. Berlin: Springer, Goodman, D.J.; Myers, R.A G Cellular standards and patents, Wireless Networks, Communications and Mobile Computing 2005 International Conference, pp vol.1. Graevenitz G.,Wagner S., Harhoff D How to measure patent thickets--a novel approach, Economics Letters, Volume 111, Issue 1, Pages 6-9. Hall, Bronwyn H, Ziedonis, R.H The patent paradox revisited: an empirical study of patenting in the U.S. semiconductor industry , Rand Journal of Economics, 36 (1), pp

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